Evidence map›Paper›PMID 36266307›Full record

ArticleScientific reports2022

Quantitatively evaluate the impact of domestic aviation control measures on the spread of COVID-19 in China.

Yu Wang, Ke Li, Ting Yuan, Yi Liu

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yu WangCenter for Applied Statistics, Renmin University of China, Beijing, 100872, China.
Ke LiSchool of Statistics, Renmin University of China, Beijing, 100872, China.
Ting YuanKey Laboratory of Civil Aviation Data Governance and Decision Optimization, Civil Aviation Management Institute of China, Beijing, 100102, China.
Yi LiuKey Laboratory of Civil Aviation Data Governance and Decision Optimization, Civil Aviation Management Institute of China, Beijing, 100102, China. liuyi@camic.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To quantitatively evaluate the impact of domestic aviation control measures on the spread of COVID-19 in China. The number of international flights from March to September 2019 simulated the number of flights from March to September 2020 without implementing aviation control measures. In addition, the proportion of asymptomatic persons and the delay in case reporting were adjusted to estimate the prevalence of each country during the same period and calculate the estimated imported cases. The estimated imported cases were assigned each day with weight, and the estimated daily reported cases were obtained based on the actual daily number of domestic cases in China. Effective Reproduction Number ([Formula: see text]) was calculated based on delayed distribution, Basic Reproductive Number ([Formula: see text]) distribution, and generation time distribution were reported in previous studies. Gaussian Process was used to estimate the effect of time-varying on [Formula: see text], and the estimated [Formula: see text] was compared with the actual [Formula: see text]. The estimated imported cases increased significantly compared with the actual number of imported cases. The estimated imported cases were mainly concentrated in North America and Europe from March to April and gradually increased in many East Asian countries from May to September. The difference between predicted [Formula: see text] and actual [Formula: see text] was statistically significant. The estimated imported cases and the estimated [Formula: see text] have increased compared to the actual situation. This paper quantitatively proves that Chinese aviation control measures significantly suppress the COVID-19 epidemic, which is conducive to promoting and applying this measure.

Indexed as

AviationCOVID-19EpidemicsBasic Reproduction NumberChinaHumans

Identifiers

PMID36266307
PMCPMC9584274

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.